Figure 5
From: An investigation of supervector regression for forensic voice comparison on small data
Pooled results for validity and reliability across the six permutations. Pooled results for validity (C llr mean) and reliability (95% CI) across the six permutations for the various sparse regression solutions utilizing the s x(1) (i.e. a-d), s ℓ1 (i.e. e-h), s ℓ2 (i.e. i-l), and s Bnormℓ2 (i.e. m-p) scoring methods, evaluated on the 60 female speaker database under studio-clean (top row), degraded mobile to landline (second row from top) and mismatched (third row from top) conditions and 90 male speaker database under studio-clean (bottom row) conditions. The various configurations are denoted as follows: circle: GMM-UBM, square: s SVM, upward-pointing triangle: coordinate descent (CD) α = 0, downward-pointing triangle: coordinate descent (CD) α = 1, right-pointing triangle: gradient projection (GP), left-pointing triangle: LS, plus: s PNN_mean, asterisk: s PNN_max, cross: s PNN_min. Note that the GMM-UBM, s SVM, s PNN_mean, s PNN_max and s PNN_min configurations do not change across the plots in the same row, as these do not use sparse representation regression methods.